crawl, walk, run: how to get started with hadoop
TRANSCRIPT
Grab some
coffee and
enjoy the
pre-show
banter before
the top of the
hour!
The Briefing Room
Crawl, Walk, Run: How to Get Started with Hadoop
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Reveal the essential characteristics of enterprise software, good and bad
Provide a forum for detailed analysis of today’s innovative technologies
Give vendors a chance to explain their product to savvy analysts
Allow audience members to pose serious questions... and get answers!
Mission
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Topics
This Month: HADOOP ECOSYSTEM
February: DATA IN MOTION
January: ANALYTICS
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The Up Sides of Disruption
….Splice Machine?
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Analyst: William McKnight
William is President of McKnight Consulting Group. His clients have included 17 of the Global 2000. Many clients have gone public with their success story. His team's implementations have won multiple Best Practices awards. William is an Entrepreneur of the Year Finalist, a frequent best practices judge and an expert witness. He has hundreds of articles and dozens of white papers in publication. William has also given numerous keynote presentations worldwide at major conferences and has given hundreds of public seminars and webinars. William’s experience includes taking his company to placement on the Inc. 500 and the Dallas 100 to seller of a multi-million dollar consulting firm. He is a passionate communicator and motivator, and a former IT VP of a Fortune 50 company.
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Splice Machine
Splice Machine is a SQL-on-Hadoop database
The product is ACID-compliant and can power both OLAP and OLTP workloads
Splice Machine is built on Java-based Apache Derby and Hbase/Hadoop
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Guest: Rich Reimer
Rich Reimer, VP of Marketing and Product Management Rich has over 15 years of sales, marketing and management experience in high-tech companies. Before joining Splice Machine, Rich worked at Zynga as the Treasure Isle studio head, where he used petabytes of data from millions of daily users to optimize the business in real-time. Prior to Zynga, he was the COO and co-founder of a social media platform named Grouply. Before founding Grouply, Rich held executive positions at Siebel Systems, Blue Martini Software and Oracle Corporation as well as sales and marketing positions at General Electric and Bell Atlantic.
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Perceptions & Questions
Analyst: William McKnight
Source: Intel
WHAT HAPPENS IN AN INTERNET MINUTE
FUELED BY DISRUPTIVE TECHNOLOGY FACTORS
Social Media
Cloud Computing
Mobile
Internet of Things
Big Data is the next Natural Resource “We have for the first time an economy based on a key resource (Information)
that is not only renewable, but self-generating.
Running out of it is not a problem, but drowning in it is.” — John Naisbitt
Transactional & Application Data
Machine Data Social Data Enterprise Content
• Volume • Structured
• Throughput
• Velocity • Structured
• Ingestion
• Variety • Unstructured
• Veracity
• Variety • Unstructured
• Volume
BIG DATA IS ADDITIVE TO EXISTING DATA
IF THIS WERE EASY, EVERYONE WOULD ALREADY BE LEVERAGING BIG DATA
“Big Data offers big business gains but hidden costs and complexity present barriers that most organizations will struggle with”
- The Cost of Big Data, Eric Savitz, Forbes 5/2012
§ Big data skills are in short supply § Custom built solutions lack integrated management § Companies need to get used to the open source nature of the software
that is enhanced by committers § Requires integration effort within the existing analytic ecosystem § Big data will be less valuable per capita than other data
Source: 603 global decision-makers involved in business intelligence, data management, and governance initiatives Source: Forrsights Strategy Spotlight: Business Intelligence And Big Data, Q4 2012
14%
19%
3%
8%
7%
7%
21%
13%
“What best describes your firm’s current usage/plans to adopt big data technologies and solutions?”
Planning to implement in more than 1 year
Planning to implement in the next 12 months
Implemented, not expanding
Expanding/upgrading implementation
Average performers are
thinking about big data
Top performers are expanding their big data
implementations
Rest of organizations
(<15% growth) (N = 482)
High performance (>15% growth)
(N = 58)
TOP PERFORMERS (GREATER THAN 15% ANNUAL GROWTH) REALIZE THEY NEED MORE
VEHICLES FOR BIG DATA
Data Warehouse
Regional and Departmental
Views
ADS
Applications & Engines
Operational Analytics & Hot Views
Data Marts Independent
Dependent
Relational Data
Conformed Dimensions
Last Year
This Year
Next Year
THE EVER-EXPANDING DATA WAREHOUSE
• Enterprise Data Warehouse users face huge annual upgrade expenses
• To avoid this spend, organizations are looking for lower cost alternatives
• Movement of data to tape not desired, because data is offline and not available for analytics
• Moving infrequently used data to Hadoop is a cost-effective, online option that preserves ability to query
Cost
On the slide with the sad people overwhelming their RDBMS… how do we know when scale up has become cost prohibitive?
What data should get moved to the data warehouses and data marts and what data is fine left in the data lake?
Isn’t SQL-on-Hadoop SQL on HDFS? How is Splice Machine, as a SQL-on-Hadoop solution, giving the ‘best of
both worlds’? How do you get data with schema into the flat files of HDFS without ‘data
page’ style formatting? Is the best advantage of SQL-on-Hadoop having the full transformation
capabilities of ETL or ELT on the data? Is a data lake the best ‘on-ramp’ to big data or is data archival off RDBMS?
QUESTIONS FOR SPLICE MACHINE
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Upcoming Topics
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This Month: HADOOP ECOSYSTEM
February: DATA IN MOTION
January: ANALYTICS
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THANK YOU for your
ATTENTION!
Some images provided courtesy of Wikimedia Commons and Wikipedia